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Improving doc
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@ -513,7 +513,7 @@ The \sc{Eigen} web site is <A HREF="http://eigen.tuxfamily.org">`http://eigen.tu
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\sc{Lapack} is a `Fortran` library for linear algebra.
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In \cgal, \sc{Lapack} is an alternative to \sc{Eigen} for singular value decomposition for the \ref
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kgJet_fitting_3 and the \ref PkgRidges_3 packages.
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PkgJet_fitting_3 and the \ref PkgRidges_3 packages.
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The \sc{Lapack} web site is <A HREF="http://www.netlib.org/lapack/">`http://www.netlib.org/lapack/`</A>.
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@ -71,7 +71,6 @@ can be omitted: if Eigen 3 (or greater) is available and
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implementation `Internal_diagonalize_traits` is used.
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\cgalHeading{Requirements}
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<OL>
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@ -27,6 +27,7 @@
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\cgalPkgSummaryEnd
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\cgalPkgShortInfoBegin
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\cgalPkgSince{3.2}
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\cgalPkgDependsOn{\ref PkgSolverSummary}
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\cgalPkgBib{cgal:ap-pcad}
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\cgalPkgLicense{\ref licensesGPL "GPL"}
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\cgalPkgDemo{Principal Component Analysis,pca.zip,Operations on Polygons,polygon.zip,Operations on Polyhedra,polyhedron_3.zip}
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@ -13,9 +13,8 @@ available on the system.
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\cgalModels `DiagonalizeTraits`
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`FT`: floating type
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`dim`: dimension of the matrices and vectors
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\tparam FT Number type
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\tparam dim Dimension of the matrices and vectors
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\sa http://eigen.tuxfamily.org
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@ -10,8 +10,7 @@ The version 3.1 (or greater) of \ref thirdpartyEigen "Eigen" must be available o
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\cgalModels `SparseLinearAlgebraTraitsWithFactor_d` and `NormalEquationSparseLinearAlgebraTraits_d`
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`T`: a sparse solver of \ref thirdpartyEigen "Eigen". The default solver is the iterative bi-congugate gradient stabilized solver
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`Eigen::BiCGSTAB` for `double`.
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\tparam T A sparse solver of \ref thirdpartyEigen "Eigen". The default solver is the iterative bi-congugate gradient stabilized solver `Eigen::BiCGSTAB` for `double`.
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\sa `CGAL::Eigen_sparse_matrix<T>`
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\sa `CGAL::Eigen_sparse_symmetric_matrix<T>`
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@ -9,10 +9,8 @@ Matrices.
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\cgalModels `DiagonalizeTraits`
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`FT`: floating type
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`dim`: dimension of the matrices and vectors
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\tparam FT Number type
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\tparam dim Dimension of the matrices and vectors
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Example
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--------------
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@ -25,10 +25,11 @@
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## Concepts ##
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- `DiagonalizeTraits`
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- `SparseLinearAlgebraTraits_d`
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- `SparseLinearAlgebraTraitsWithFactor_d`
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- `SvdTraits`
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- `DiagonalizeTraits`
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## Classes ##
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@ -3,4 +3,3 @@ Kernel_23
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STL_Extension
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Algebraic_foundations
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Miscellany
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Jet_fitting_3
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@ -1,6 +1,3 @@
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#include <set>
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#include <CGAL/Simple_cartesian.h>
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#include <CGAL/Eigen_solver_traits.h>
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#include <CGAL/Eigen_matrix.h>
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@ -21,6 +18,8 @@ int main(void)
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Eigen_matrix A (degree);
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Eigen_vector diag (degree);
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// Randomly make some coefficients of the matrix non-zero
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for (std::size_t i = 0; i < nb_nonzero_coef; ++ i)
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{
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std::size_t x = rand () % degree;
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@ -38,7 +37,8 @@ int main(void)
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for (std::size_t i = 0; i < degree; ++ i)
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A.add_coef (i, i, diag.vector()[i]);
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// Create sparse matrix
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A.assemble_matrix();
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Eigen_vector X (degree);
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@ -760,11 +760,6 @@ Square, circular and two-points border parameterizations are good starting point
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Obviously, this package would benefit of having robust algorithms
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which transform arbitrary meshes into topological disks.
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\example Surface_mesh_parameterization/Simple_parameterization.cpp
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\example Surface_mesh_parameterization/Mesh_cutting_parameterization.cpp
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\example Surface_mesh_parameterization/Complete_parameterization_example.cpp
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\example Surface_mesh_parameterization/polyhedron_ex_parameterization.cpp
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*/
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} /* namespace CGAL */
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@ -1,5 +1,6 @@
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/// \example Surface_mesh_parameterization/Simple_parameterization.cpp
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/// \example Surface_mesh_parameterization/Mesh_cutting_parameterization.cpp
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/// \example Surface_mesh_parameterization/Complete_parameterization_example.cpp
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/// \example Surface_mesh_parameterization/Eigen_parameterization.cpp
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/// \example Surface_mesh_parameterization/polyhedron_ex_parameterization.cpp
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/*!
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\example Surface_mesh_parameterization/Simple_parameterization.cpp
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\example Surface_mesh_parameterization/Mesh_cutting_parameterization.cpp
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\example Surface_mesh_parameterization/Complete_parameterization_example.cpp
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\example Surface_mesh_parameterization/polyhedron_ex_parameterization.cpp
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*/
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